Live television, video on-demand, and other media and content services deliver value and generate revenue by building a large audience that consumes the service's content regularly. Operators employ various methods to engage customers to the content, in order to create both new revenue and maintain active subscriptions.
One method for engaging customers is to promote relevant content. Operators can do this through a combination of editorial selection or automatic solutions that generate a list of content recommendations the customer is more likely to consume. These methods typically consist of generating and presenting lists of recommended content.
In some cases, many consumers share a single subscription to a content service in a group, such as a household. Various methods are currently used to recommend content to such consumers. One method of recommendation is the use of a collective identity, i.e. the consumers who share the subscription are treated as a single entity for the purposes of recommending content, and all users are recommended the same content. However, when all consumers are linked to a single identity or profile, the recommendations made may be biased towards those consumers (e.g., children) who predominantly utilize the service.
Another method of recommendation is to have each consumer create a “sub-profile” so that content is personalized towards that “sub-profile.” When a user uses the service, it asks the user to select a “sub-profile” to use. Typically, such a system can only accommodate a single user and “sub-profile” at once.
Yet another method is to have a profile linked to each device configured to output the content for the subscription service. Thus, the recommendations are based on the viewing history on the device. Such a configuration is based primarily on the viewing history at the location of the device, and may be limited to providing relevant recommendations to those consumers who use that particular device most often.